Industry focus: Pharma & Biotech R&D
AI drug discovery for Pharma R&D.
Deploy regulated AI for pharma spanning AI drug discovery workflows and trial operations. We accelerate artificial intelligence drug discovery with governance your QA, security, and regulatory teams can defend.
- Navigate complex protocols with AI for drug discovery copilots.
- Use AI in drug development agents to reduce manual burden across study startup.
- Keep sensitive drug discovery AI data inside compliant environments with clear governance.
- Move beyond AI drug discovery companies pilots to broad adoption of production-grade services.
For R&D, clinical operations & digital teams in life sciences
Discovery & literature
→ synthesis copilots, cited
Study startup & trials
→ agentic feasibility workflows
Evidence & analysis
→ governed Q&A over R&D reports
Regulatory & submission
→ consistency & cross-ref checks
The R&D reality
Complex, regulated, and overloaded.
Pharma and biotech R&D runs on multi-year programs with complex protocols, distributed teams, and continuously evolving requirements.
Heavy documentation and evidence requirements span preclinical through regulatory submission, with constant coordination between science, clinical operations, regulatory affairs, and external partners.
AI's potential is real, but so are the risks. Kriv AI focuses on governed AI patterns that respect these constraints.
Sound familiar?
Mountains of regulated content
Protocols, reports, and publications pile up faster than any team can keep up with, and the answers are buried inside them.
Slow, manual study startup
Feasibility and study-startup processes are slow and manually driven, gated by documentation load rather than science.
Spreadsheets and scripts that don't scale
Teams build local spreadsheets and one-off scripts that don't scale, can't be governed, and quietly become shadow AI.
Compliance is wary of generative AI
Hallucinations, confidentiality breaches, and misinterpretations have real consequences, so QA and regulatory keep generative AI at arm's length from regulated content.
Who we work with
From research leadership to clinical operations and digital teams.
R&D & Clinical Development Leaders
- Heads of R&D, Clinical Development, Translational Medicine.
- Need better visibility, faster insight generation, and less manual friction.
- Want AI that supports, not replaces, expert judgment.
Clinical Operations & Study Teams
- Study start-up, feasibility, and operations managers.
- Coordinate protocols, sites, and timelines under intense documentation load.
- Need automation and copilots that fit into existing tools and SOPs.
Data Science, Analytics & Digital
- R&D data science, AI, and digital transformation teams.
- Already experimenting with LLMs and automation, but need governance and production patterns.
- Want to avoid shadow AI and fragile prototypes.
How we help
Governed AI for the unique needs of pharma and biotech research.
AI Readiness & Governance Assessment
Assess where AI can safely accelerate R&D workflows, from literature synthesis to study operations, while respecting regulatory constraints.
AI Readiness & GovernanceAgentic AI & Automation
Design agents for protocol workflows, document routing, checklists, and orchestration around study startup and operations.
Agentic AI & AutomationLLM Fine-Tuning & Custom Models
Tune models on your protocols, internal reports, submissions, and curated evidence to power domain-accurate copilots.
LLM Fine-Tuning & Custom ModelsMLOps & Governance-as-a-Service
Keep R&D AI services monitored, governed, and explainable, so they can survive audits and leadership scrutiny.
MLOps & Governance-as-a-ServiceAI Governance & Compliance-as-a-Service
Define policies, risk classifications, and approvals for AI in R&D contexts, aligned with your existing QA and regulatory frameworks.
AI Governance & ComplianceExample use cases
Practical AI use cases across Pharma R&D.
Pick a workflow, see what the governed AI assist actually looks like in practice.
Protocol & Study Document Copilot
LLM-based assistants that help teams navigate protocols, amendments, and SOPs with citations and guardrails.
- Answers grounded in the source document, with citations
- Amendment and SOP cross-referencing
- Guardrails that keep the model inside approved content
Regulated & confidential data
Your scientific IP and clinical data deserve serious protection.
R&D data often touches clinical data, patient information, proprietary science, and confidential IP.
Kriv AI designs deployment patterns that keep these assets in controlled environments, your cloud, your access controls, your audit logs.
Governance extends beyond model behavior to confidentiality and information security, ensuring that AI doesn't become a vector for data leakage.
What this means in practice
- Architectures that prioritize your cloud, VPCs, and access controls.
- Patterns for de-identification or minimization when PHI appears in R&D workflows.
- Logging of AI interactions for audit and internal QA.
- Clear boundaries for what AI agents are allowed to access and do.
How we work with R&D teams
A structured approach that respects the complexity of pharma R&D.
Use Case Discovery & Prioritization
- Workshop with R&D, clinical ops, and compliance to identify high-value, feasible use cases.
- Balance ambition with regulatory and operational realities.
Design & Pilot with Domain Experts
- Co-design workflows and AI behavior with R&D and operations stakeholders.
- Run pilots where human experts stay firmly in control of decisions.
Hardening & Governance
- Harden successful pilots into governed services with monitoring, access control, and documentation.
- Align with your existing QA, validation, and change-control processes.
Scale to the R&D Portfolio
- Extend proven patterns to adjacent teams, studies, or assets.
- Refine governance and playbooks as more use cases come online.
What you get
What R&D leaders aim to achieve.
6
governed R&D use cases, from protocol copilots to signal intake
5
solution tracks spanning readiness, agents, MLOps, and governance
100%
of AI interactions logged for audit and internal QA
Faster, better-informed work
Reduce time spent hunting for information and reconciling documents.
Reduced manual overhead
Offload repetitive, documentation-heavy tasks to governed AI workflows.
More trustworthy AI in R&D
Keep humans in the loop, with guardrails that build trust rather than skepticism.
R&D AI you can explain
Show leadership and regulators how AI is used, controlled, and monitored across R&D.
Go deeper
Resources for Pharma & Biotech R&D.
Insights, guides, and case studies relevant to R&D teams.
Straight answers
Pharma R&D & governance questions
Will AI replace the judgment of our scientists and clinical teams?
No. Every pattern we design keeps human experts firmly in control of decisions. The AI accelerates literature triage, document navigation, and study-startup coordination, but approvals, interpretations, and regulatory decisions stay with your people.
How do you keep confidential R&D data and IP protected?
We design deployment patterns that keep clinical data, patient information, and proprietary science inside controlled environments, your cloud, your VPCs, your access controls, your audit logs. Governance covers confidentiality and information security, not just model behaviour, so AI never becomes a vector for data leakage.
How does this fit our GxP, QA, and regulatory frameworks?
We align with your existing QA, validation, and change-control processes rather than working around them. Patterns are designed to support GxP-aligned, 21 CFR Part 11, and ICH E6 expectations, with logging of AI interactions for audit and internal QA.
We already have AI pilots and scripts. What happens to them?
Good, we can assess them. We identify what is worth salvaging and design a path from fragile prototypes and shadow AI to governed, production-grade services with monitoring, access control, and documentation.
How do you handle PHI when it appears in R&D workflows?
We assume regulated constraints by default and follow HIPAA-aligned practices. Where PHI appears, we apply de-identification or minimization patterns and scope exactly what AI agents are allowed to access and do.
Where do most R&D teams start with you?
Usually a focused AI Readiness & Governance assessment or a single high-value workflow, a protocol copilot, literature review assistant, or study-startup automation. Once a pilot proves out under governance, we extend the proven pattern to adjacent teams, studies, or assets.
How long until our teams see value?
We start with a discovery and prioritization workshop, then design and pilot with your domain experts before hardening into a governed service. The goal is a defensible pilot you can show leadership early, well ahead of any multi-year platform programme.
Start here
Want AI that actually fits pharma R&D reality?
Pilot graveyards, slow study startup, compliance wary of generative AI, bring your R&D, clinical ops, and compliance teams to a 30-minute working session and we'll map a governed path that respects science, regulation, and human expertise.
+1-732-433-5564 · info@kriv.ai · East Brunswick, NJ
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